Enterprise AI Assurance for APRA-Regulated Institutions
We help banks, insurers and superannuation funds get AI-ready, governed, and deployed — establishing risk boundaries, human-in-the-loop controls, and a policy framework aligned to APRA CPS 230 operational resilience obligations and the AU AI Safety Standard, before any agentic AI goes into production.
APRA CPS 230 and related prudential standards should be verified against APRA's current published requirements for your entity category at time of engagement.
Who This Is For
Banks & ADIs
Authorised deposit-taking institutions building agentic AI into customer-facing and back-office workflows under prudential oversight.
General & Life Insurers
Insurers deploying AI into underwriting, claims and pricing workflows that require defensible, auditable decision boundaries.
Superannuation Funds
Trustees introducing AI into member services and advice pathways while carrying member-best-interest obligations.
Other APRA-Regulated Entities
Any APRA-regulated entity needing to evidence AI governance maturity to its board, audit committee or regulator.
Why Regulated Enterprises Partner With Vertex Core
Data Platform Assessment & Uplift
AI cannot perform on dirty, fragmented, or semantically weak data. We audit your platform, map the gaps, and deliver an SSOT lakehouse blueprint with vector readiness scoring before any model is deployed.
AI Governance, Assurance & Policy Frameworks
Deploying AI without defined risk boundaries and human override controls is a compliance liability. We establish the policy guardrails, RBAC data rules, HITL triggers, and token cost controls before go-live — aligned to APRA CPS 230 and the AU AI Safety Standard.
Live Agentic AI Prototypes in 2–4 Weeks
Executive and board buy-in comes from seeing AI work, not from slide decks. Our PoC Sprint delivers a governed, multi-agent prototype on your cloud environment with real tool execution and a production roadmap.
Compliance & Assurance Capabilities
Drawn from our AI Assurance & Policy Readiness Assessment — a fixed-scope sprint establishing the governance architecture your AI needs to operate safely, and the documented evidence your audit committee, board, and regulator will require.
AI Risk Classification & Boundary Definition
Systematic classification of planned AI use cases by risk tier — from low-risk summarisation workloads to high-risk autonomous decision-making agents — defining exposure boundaries and escalation thresholds before build begins.
Human-in-the-Loop (HITL) Design
Design of human checkpoint triggers, approval workflow architecture, and override controls for agentic AI workflows — ensuring human oversight is embedded by design, not bolted on after deployment.
Data Privacy & Access Control Review
Assessment of RBAC/ABAC policy design, PII handling procedures, consent management maturity, and data access patterns for LLM and agentic AI workloads — identifying privacy leakage vectors before they reach production.
Token FinOps & Model Routing Strategy
Design of token budget governance, model tier routing policies, and FinOps guardrails so AI cost scales predictably with value rather than unbounded with usage.
Agentic Safety & Containment Architecture
Review of agent tool call permissions, blast radius containment design, sandbox boundary architecture, prompt injection defence patterns, and data leakage prevention for multi-agent systems.
Compliance Alignment Review
Structured assessment of your AI governance posture against APRA CPS 230 operational resilience obligations and the AU AI Safety Standard — producing a gap register and remediation priority stack for your audit committee.
What You Receive
- 1
AI Risk, Privacy & Compliance Boundary Report
Tiered risk classification of your AI use cases with defined exposure boundaries, compliance gaps against APRA CPS 230 and the AU AI Safety Standard, and a prioritised remediation register.
- 2
Human-in-the-Loop (HITL) Trigger & Override Matrix
Structured matrix mapping each AI workflow to its required human checkpoint, approval authority, override control, and escalation path — ready for engineering implementation.
- 3
Token FinOps & Model Routing Cost Strategy
Model routing policy design, token budget governance framework, and a cost model projecting AI operating costs at your target usage volumes.
- 4
Agentic Safety & Data Leakage Audit Framework
Documented safety architecture requirements for agentic AI deployments — tool call permission model, containment boundaries, sandbox design, and prompt injection defence patterns.
Ready for an APRA CPS 230-Aligned AI Assurance Review?
Fixed-scope, senior-led, and delivered in weeks — not quarters. Establish the governance evidence your board and regulator will require before your next agentic AI deployment.